• Lecturer of “Deep Learning” course (400+ registered students, 12 lectures, 11 coding assignments)• Organizer of special courses on Deep Learning (yearly in fall semesters)• Supervisor of 40+ Master’s theses• Research on physics-informed deep learning, unsupervised deep learning, model-based reinforcement learning• Collaborative research projects with industry (Fingrid, Neste, Nokia Bell Labs, F-Secure)

• Research on semi-supervised deep learning, perceptual grouping, model-predictive control.• Applied R&D projects on document processing and industrial process control.

Scalable machine learning group, classification tasks

Demand forecasting and recommender systems (product canibalization models, assortment recommendation)(Senior Analytics Specialist Aug 2012 - Jun 2014)

Research on unsupervised deep learning, probabilistic latent variable models, matrix factorization.

R&D projects on material recognition

Statistical signal processing, Bayesian data analysis, modeling spatio-temporal data